SOTAVerified

Question Answering

Question answering can be segmented into domain-specific tasks like community question answering and knowledge-base question answering. Popular benchmark datasets for evaluation question answering systems include SQuAD, HotPotQA, bAbI, TriviaQA, WikiQA, and many others. Models for question answering are typically evaluated on metrics like EM and F1. Some recent top performing models are T5 and XLNet.

( Image credit: SQuAD )

Papers

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Showing 2876–2900 of 10817 papers

TitleStatusHype
Answer Interaction in Non-factoid Question Answering Systems—0
AGQA: A Benchmark for Compositional Spatio-Temporal Reasoning—0
Bridging the Gap between Language Model and Reading Comprehension: Unsupervised MRC via Self-Supervision—0
Bridging the Gap Between Information Seeking and Product Search Systems: Q&A Recommendation for E-commerce—0
Answering Yes/No Questions via Question Inversion—0
Bridging Technology and Humanities: Evaluating the Impact of Large Language Models on Social Sciences Research with DeepSeek-R1—0
Answering Yes-No Questions by Penalty Scoring in History Subjects of University Entrance Examinations—0
AAD-LLM: Neural Attention-Driven Auditory Scene Understanding—0
Enhancing Multimodal LLM for Detailed and Accurate Video Captioning using Multi-Round Preference Optimization—0
Bridging Speech and Textual Pre-trained Models with Unsupervised ASR—0
Bridging Question Answering and Discourse The case of Multi-Sentence Questions—0
Answering while Summarizing: Multi-task Learning for Multi-hop QA with Evidence Extraction—0
Answering Visual What-If Questions: From Actions to Predicted Scene Descriptions—0
Bridging Information-Seeking Human Gaze and Machine Reading Comprehension—0
AGQA 2.0: An Updated Benchmark for Compositional Spatio-Temporal Reasoning—0
Bridging Context Gaps: Leveraging Coreference Resolution for Long Contextual Understanding—0
Answering Unseen Questions With Smaller Language Models Using Rationale Generation and Dense Retrieval—0
A Glimpse in ChatGPT Capabilities and its impact for AI research—0
Bridge to Answer: Structure-aware Graph Interaction Network for Video Question Answering—0
Answering Unanswered Questions through Semantic Reformulations in Spoken QA—0
A criterion for Artificial General Intelligence: hypothetic-deductive reasoning, tested on ChatGPT—0
Enhancing Multi-Image Question Answering via Submodular Subset Selection—0
Bridge the Gap between Language models and Tabular Understanding—0
Bridge Damage Cause Estimation Using Multiple Images Based on Visual Question Answering—0
Answering Science Exam Questions Using Query Reformulation with Background Knowledge—0
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All datasetsSQuAD2.0SQuAD1.1HotpotQAPIQABoolQCOPATriviaQASQuAD1.1 devNatural QuestionsOpenBookQATruthfulQAMultiRC

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1IE-Net (ensemble)EM90.94—Unverified
2FPNet (ensemble)EM90.87—Unverified
3IE-NetV2 (ensemble)EM90.86—Unverified
4SA-Net on Albert (ensemble)EM90.72—Unverified
5SA-Net-V2 (ensemble)EM90.68—Unverified
6FPNet (ensemble)EM90.6—Unverified
7Retro-Reader (ensemble)EM90.58—Unverified
8EntitySpanFocusV2 (ensemble)EM90.52—Unverified
9TransNets + SFVerifier + SFEnsembler (ensemble)EM90.49—Unverified
10EntitySpanFocus+AT (ensemble)EM90.45—Unverified